Literature DB >> 31462767

Identification of novel risk loci with shared effects on alcoholism, heroin, and methamphetamine dependence.

Yan Sun1, Suhua Chang2, Zhen Liu1, Libo Zhang1, Fan Wang3,4, Weihua Yue2, Hongqiang Sun2, Zhaojun Ni2, Xiangwen Chang1, Yibing Zhang1, Yang Chen1, Jiqiang Liu5, Lin Lu1,2, Jie Shi6,7,8,9.   

Abstract

Different substance dependences have common effects on reward pathway and molecular adaptations, however little is known regarding their shared genetic factors. We aimed to identify the risk genetic variants that are shared for substance dependence (SD). First, promising genome-wide significant loci were identified from 3296 patients (521 alcoholic/1026 heroin/1749 methamphetamine) vs 2859 healthy controls and independently replicated using 1954 patients vs 1904 controls. Second, the functional effects of promising variants on gene expression, addiction characteristics, brain structure (gray and white matter), and addiction behaviors in addiction animal models (chronic administration and self-administration) were assessed. In addition, we assessed the genetic correlation among the three SDs using LD score regression. We identified and replicated three novel loci that were associated with the common risk of heroin, methamphetamine addiction, and alcoholism: ANKS1B rs2133896 (Pmeta = 3.60 × 10-9), AGBL4 rs147247472 (Pmeta = 3.40 × 10-12), and CTNNA2 rs10196867 (Pmeta = 4.73 × 10-9). Rs2133896 in ANKS1B was associated with ANKS1B gene expression and had effects on gray matter of the left calcarine and white matter of the right superior longitudinal fasciculus in heroin dependence. Overexpression of anks1b gene in the ventral tegmental area decreased addiction vulnerability for heroin and methamphetamine in self-administration rat models. Our findings could shed light on the root cause for substance dependence and will be helpful for the development of cost-effective prevention strategies for general addiction disorders.

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Year:  2019        PMID: 31462767     DOI: 10.1038/s41380-019-0497-y

Source DB:  PubMed          Journal:  Mol Psychiatry        ISSN: 1359-4184            Impact factor:   15.992


  5 in total

Review 1.  Alcohol and the brain: from genes to circuits.

Authors:  Gabor Egervari; Cody A Siciliano; Ellanor L Whiteley; Dorit Ron
Journal:  Trends Neurosci       Date:  2021-10-23       Impact factor: 13.837

2.  Internet Addiction Increases in the General Population During COVID-19: Evidence From China.

Authors:  Yang-Yang Li; Yan Sun; Shi-Qiu Meng; Yan-Ping Bao; Jia-Lu Cheng; Xiang-Wen Chang; Mao-Sheng Ran; Yan-Kun Sun; Thomas Kosten; John Strang; Lin Lu; Jie Shi
Journal:  Am J Addict       Date:  2021-03-19

3.  Genome-wide association meta-analyses identify novel genetic risk loci and polygenic phenotype associations for heroin, methamphetamine and alcohol dependences.

Authors:  Su-Hua Chang; Yan Sun; Fan Wang; Xiang-Wen Chang; Ying-Jian Zhang; Tian-Ye Jia; Hong-Qiang Sun; Wei-Hua Yue; Ping Wu; Lin Lu; Jie Shi
Journal:  Clin Transl Med       Date:  2022-01

Review 4.  Genetics of methamphetamine use disorder: A systematic review and meta-analyses of gene association studies.

Authors:  Alexandre A Guerin; Eric J Nestler; Michael Berk; Andrew J Lawrence; Susan L Rossell; Jee Hyun Kim
Journal:  Neurosci Biobehav Rev       Date:  2020-11-17       Impact factor: 8.989

5.  Sex-specific nicotine sensitization and imprinting of self-administration in rats inform GWAS findings on human addiction phenotypes.

Authors:  Alena Kozlova; Robert R Butler; Siwei Zhang; Thomas Ujas; Hanwen Zhang; Stephan Steidl; Alan R Sanders; Zhiping P Pang; Paul Vezina; Jubao Duan
Journal:  Neuropsychopharmacology       Date:  2021-05-18       Impact factor: 7.853

  5 in total

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